IoT connectivity
Connect machines, PLCs, gateways, and sensor streams through MQTT-ready ingestion pipelines.
Industrial AI for connected production lines
AI monitoring for connected factories.
ComizAI connects IoT sensors and machines, collects real-time industrial data, detects anomalies with machine learning, and gives teams a reliable dashboard for predictive maintenance.
24/7
telemetry ingestion
ML alerts
before failures spread
Cloud ready
from pilot to plant scale
Anomaly score
Machine health
82%
74%
41%
91%
Platform capabilities
Industrial data, machine learning, and maintenance workflows in one place.
Built for teams that need reliable sensor ingestion, fast visibility, and actionable anomaly signals across production assets.
Real-time monitoring
Track live temperature, vibration, throughput, and operating states from a unified control view.
AI anomaly detection
Use machine learning models to flag abnormal behavior before it becomes unplanned downtime.
Scalable cloud architecture
Deploy containerized services that grow from a single pilot line to multi-site production fleets.
How it works
From machine signal to maintenance decision.
ComizAI turns raw plant data into operational clarity through a focused three-stage pipeline.
Data collection
IoT sensors and machine gateways stream temperature, vibration, and production events into the platform.
Data processing
Backend services normalize incoming telemetry, store time-series records, and prepare signals for analysis.
AI analysis and dashboard
Models score anomalies and deliver dashboard insights for predictive maintenance and faster action.
Demo preview
Live health signals for critical machines.
Monitor telemetry, spot abnormal patterns, and prioritize maintenance from an operations-ready dashboard.
Temperature
72.4°C
Stable
Vibration
4.8 mm/s
Rising
Anomaly status
Watch zone
Review
anomaly spike
Asset
Compressor C-12
Model score
0.86 risk
Next action
Inspect bearing
ETA to service
18 hours
Business impact
Maintenance teams get earlier signals and clearer priorities.
Designed for production leaders, maintenance engineers, and data teams working toward measurable uptime gains.
Reduce downtime
Identify degradation patterns early and plan interventions before a line stoppage occurs.
Improve maintenance efficiency
Prioritize work orders with model-backed risk signals and real operating context.
Real-time visibility
Give teams a shared view of machine health, anomalies, and production-critical metrics.
Tech stack
A practical architecture for industrial pilots and cloud scale.
ComizAI uses familiar technologies that make integration, deployment, and iteration straightforward.
MQTT
Python / Flask
Machine Learning
Docker / Cloud
Bring predictive monitoring to your production line.
Start with a focused pilot, connect your first machines, and turn operational data into measurable maintenance decisions.
Human behind the platform
About the Founder
ComizAI was founded by Mohammed OUIYZME, an Industrial IT and Industry 4.0 engineer based in Lille, France.
His work connects IoT sensors, MQTT/API pipelines, Flask backends, and machine learning for predictive maintenance.
With ComizAI, he turns a hands-on IT/OT background into a clear SaaS platform for modern factories.
Lille, France · Industrial IoT · AI monitoring